Forecast models to predict the demand for endoscopic procedures in a tertiary unit: a prospective validation

Area of Science:

• Gastroenterology and Health Services Research

Background:

• Endoscopic procedure utilization has grown exponentially.
• Accurate demand prediction is vital for endoscopy unit capacity planning and resource allocation.
• Current endoscopy software lacks integrated predictive modeling capabilities.

Purpose of the Study:

• To develop and validate forecast models for predicting endoscopy demand.
• To address the limitation of absent predictive models in current endoscopy software.
• To improve resource allocation and capacity planning in endoscopic units.

Main Methods:

• Utilized historical endoscopy demand data from a tertiary unit spanning 2015-2021 (83 months).
• Developed forecast models employing exponential smoothing techniques.
• Adjusted models for trend and seasonality components.

Main Results:

• Successfully developed predictive models for endoscopy demand forecasting.
• Demonstrated the feasibility of applying exponential smoothing for trend and seasonality.
• Models were derived from a substantial dataset covering 83 months.

Conclusions:

• Developed forecast models can aid in effective capacity planning for endoscopy units.
• The integration of predictive models can enhance resource allocation efficiency.
• This approach addresses a critical need for data-driven decision-making in endoscopy services.